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A Symmetric Multivariate Leakage Correction for MEG Connectomes

G.L. Colclough, M.J. Brookes, S.M. Smith, M.W. Woolrich

Ambiguities in the source reconstruction of magnetoencephalographic (MEG) measurements can cause spurious
correlations between estimated source time-courses. In this paper, we propose a symmetric orthogonalisation
method to correct for these artificial correlations between a set of multiple regions of interest (ROIs). This process
enables the straightforward application of network modelling methods, including partial correlation or multivariate
autoregressive modelling, to infer connectomes, or functional networks, from the corrected ROIs. Here, we
apply the correction to simulated MEG recordings of simple networks and to a resting-state dataset collected
from eight subjects, before computing the partial correlations between power envelopes of the corrected
ROItime-courses. We show accurate reconstruction of our simulated networks, and in the analysis of real
MEGresting-state connectivity, we find dense bilateral connections within the motor and visual networks, together
with longer-range direct fronto-parietal connections